Agent Skills: langgraph-docs

Fetches and references LangGraph Python documentation to build stateful agents, create multi-agent workflows, and implement human-in-the-loop patterns. Use when the user asks about LangGraph, graph agents, state machines, agent orchestration, LangGraph API, or needs LangGraph implementation guidance.

UncategorizedID: langchain-ai/deepagents/langgraph-docs

Install this agent skill to your local

pnpm dlx add-skill https://github.com/langchain-ai/deepagents/tree/HEAD/libs/cli/examples/skills/langgraph-docs

Skill Files

Browse the full folder contents for langgraph-docs.

Download Skill

Loading file tree…

libs/cli/examples/skills/langgraph-docs/SKILL.md

Skill Metadata

Name
langgraph-docs
Description
Fetches and references LangGraph Python documentation to build stateful agents, create multi-agent workflows, and implement human-in-the-loop patterns. Use when the user asks about LangGraph, graph agents, state machines, agent orchestration, LangGraph API, or needs LangGraph implementation guidance.

langgraph-docs

Workflow

1. Fetch the Documentation Index

Use fetch_url to read: https://docs.langchain.com/llms.txt

This returns a structured list of all available documentation with descriptions.

2. Select Relevant Documentation

Identify 2-4 most relevant URLs from the index. Prioritize:

  • Implementation questions — specific how-to guides
  • Conceptual questions — core concept pages
  • End-to-end examples — tutorials
  • API details — reference docs

3. Fetch and Apply

Use fetch_url on the selected URLs, then complete the user's request using the documentation content.

If fetch_url fails or returns empty content, retry once. If it fails again, inform the user and suggest checking https://langchain-ai.github.io/langgraph/ directly.